CA3064137A1 - Method and device for recommending information - Google Patents

Method and device for recommending information Download PDF

Info

Publication number
CA3064137A1
CA3064137A1 CA3064137A CA3064137A CA3064137A1 CA 3064137 A1 CA3064137 A1 CA 3064137A1 CA 3064137 A CA3064137 A CA 3064137A CA 3064137 A CA3064137 A CA 3064137A CA 3064137 A1 CA3064137 A1 CA 3064137A1
Authority
CA
Canada
Prior art keywords
user
time
region
track
unfamiliar
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CA3064137A
Other languages
French (fr)
Inventor
Jiangyi XU
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
10353744 Canada Ltd
Original Assignee
10353744 Canada Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 10353744 Canada Ltd filed Critical 10353744 Canada Ltd
Publication of CA3064137A1 publication Critical patent/CA3064137A1/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9535Search customisation based on user profiles and personalisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241Advertisements
    • G06Q30/0251Targeted advertisements
    • G06Q30/0261Targeted advertisements based on user location
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29Geographical information databases
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9537Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241Advertisements
    • G06Q30/0251Targeted advertisements
    • G06Q30/0255Targeted advertisements based on user history
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/021Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences

Abstract

Provided are a method and device for recommending information. According to one embodiment of the present invention, the method comprises: acquiring a current time and a current geographical region in which a user is located; and if the current time falls within an active time range of the user and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region. The embodiment of the present invention realizes accurate distribution of POI information while reducing inefficient use of a network resource and disturbance to a user resulting from recommendation of irrelevant POI information.

Description

METHOD AND DEVICE FOR RECOMMENDING INFORMATION
Cross-reference to related applications [01] This patent application claims the priority of the Chinese patent application entitled "Method and device for recommending information", which was filed on June 26, 2017, with the application number 201710496441.9. The entire text of this application is hereby incorporated in its entirety by reference.
Technical Field
[02] The present application relates to the field of geographic information technology, and in particular, to a method and device for recommending information.
Background Art
[03] POI (Point of Interest) is a term in a geographic information system (GIS). It refers to a geographic object that can be abstracted into a point, especially a geographic entity closely related to people's lives, such as a school, a bank, a restaurant, a gas station, a hospital, a supermarket, and the like.
[04] With the rapid development of the mobile terminal and the communication technology, when a user uses an APP (Application) in a mobile terminal, the APP in the mobile terminal may acquire the current location of the user and recommend the POI(s) near the current location to the user, such as restaurants, gas stations, supermarkets, and the like, so as to bring great convenience to users' lives.
[05] The existing POI recommendation methods are usually based on the user's geographic location. However, if the user is in a relatively familiar area and is familiar with the nearby POIs, such as the user's workplace or home, or if the user does not have a willingness to consume or make any purchase, in such cases, when a POI recommendation is made to the user, the POI
information may not only waste network resources in its transmission process, but also cause unnecessary interruptions to the user.

Summary of the Invention
[06] In view of the above problems, the present application has been made in order to provide a method and device for recommending information that can overcome the above problems or at least partially solves the above problems.
[07] According to one aspect of the present invention, a method for recommending information, characterized in that the method comprises:
[08] obtaining a current time and a current geographical region in which a user is located;
[09] if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region.
[10] Optionally, the active time range of the user can be obtained through the following method:
[11] obtaining a historical access log of the user within a preset time period;
[12] extracting access time points corresponding to the historical access log;
clustering the extracted access time points to obtain a time point set satisfying a first density condition, wherein the first density condition comprises: the time point set comprises access time points in a number exceeding a first threshold, a time interval between any two access time points in the time point set is less than a preset interval;
[13] counting the access time points in the time point set to determine the active time range of the user.
[14] Optionally, the unfamiliar region of the user can be obtained through the following method:
[15] obtaining the historical access log of the user within a preset time period; and determining a location track corresponding to the historical access log;
[16] clustering track points in the determined location track according to latitude and longitude thereof to obtain a track point set satisfying a second density condition, wherein the second density condition comprises: track points in a number of more than a second threshold existing in a present coverage range with any one of the track points in the track point set as a circular center;
[17] determining the unfamiliar region of the user according to the latitude and longitude of the track points in the track point set.
[18] Optionally, the method further comprises:
[19] collecting the historical access log of the user, wherein the historical access log comprises at least a user identifier, an access time, and a location track corresponding to the user access behavior;
[20] uploading, to the server, the historical access log of the user, so that the server determines the active time range and the unfamiliar region of the user according to the historical access log;
[21] obtaining the active time range and the unfamiliar region of the user from the server.
[22] Optionally, the method further comprises:
[23] obtaining a dwell time of the user in the current geographical region if the current time is within an active time range of the user and the current geographical region is an unfamiliar region of the user; if the dwell time exceeds a preset time threshold, recommending, to the user, information of the point of interest (POI) in the current geographical region.
[24] According to one aspect of the present invention, a device for recommending information is provided, the device comprising:
[25] a first obtaining module, which is used for obtaining a current time and a current geographical region in which a user is located;
[26] a first recommending module, which is used for, if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region.
[27] Optionally, the device further comprises:
[28] an active time range determining module, which is used for determining the active time range of the user;
[29] the active time range determining module comprises:
[30] a first obtaining submodule, which is used for obtaining a historical access log of the user within a preset time period, and extracting access time points corresponding to the historical access log;
[31] a first clustering submodule, which is used for clustering the extracted access time points to obtain a time point set satisfying a first density condition, wherein the first density condition comprises: the time point set comprises access time points in a number exceeding a first threshold, and a time interval between any two access time points in the time point set is less than a preset interval;
[32] a first counting submodule, which is used for counting the access time points in the time point set to determine the active time range of the user.
[33] Optionally, the device further comprises:
[34] an unfamiliar region determining module, which is used for determining an unfamiliar region of the user;
[35] the unfamiliar region determining module comprises:
[36] a second obtaining submodule, which is used for obtaining the historical access log of the user within a preset time period, and determining a location track corresponding to the historical access log;
[37] a second clustering submodule, which is used for clustering track points in the determined location track according to latitude and longitude thereof to obtain a track point set satisfying a second density condition, wherein the second density condition comprises:
track points in a number of more than a second threshold existing in a present coverage range with any one of the track points in the track point set as a circular center;
[38] a second counting submodule, which is used for determining the unfamiliar region of the user according to the latitude and longitude of the track points in the track point set.
[39] Optionally, the device further comprises:
[40] a collecting module, which is used for collecting the historical access log of the user, wherein the historical access log comprises at least a user identifier, an access time, and a location track corresponding to the user access behavior;
[41] an uploading module, which is used for uploading, to the server, the historical access log of the user, so that the server determines the active time range and the unfamiliar region of the user according to the historical access log; a second obtaining module, which is used for obtaining the active time range and the unfamiliar region of the user from the server.
[42] Optionally, the device further comprises:
[43] a second recommending module, which is used for obtaining a dwell time of the user in the current geographical region if the current time is within an active time range of the user and the current geographical region is an unfamiliar region to the user; and if the dwell time exceeds a preset time threshold, recommending, to the user, information of the point of interest (POI) in the current geographical region.
[44] According to another aspect of the present invention, a computing device is provided, comprising: a memory, a processor, and a program stored on the memory and executable on the processor, characterized in that the processor executes the program to implement the steps in the method for recommending information as mentioned above.
[45] According to another aspect of the present invention, a computer readable storage medium having stored thereon a program is provided; the program is executed by a processor to implement the steps in the method for recommending information as mentioned above.
[46] According to a method and device for recommending information provided by some embodiments of the present invention, on the basis of the existing POI
information recommendation based on the geographic location of a user, the method further determines whether the user has the need for POI information according to the current time and the current geographic location of the user. More specifically, if the current time is within an active time range of the user, and the current geographical region is an unfamiliar region to the user, it can be considered that the user may have a need for POI information. In such a case, the user is recommended with the POI information of the current geographical region, which not only can accurately deliver the POI information, but also can reduce the waste of network resources and avoid interrupting the user with irrelevant POI information recommendation.
[47] The above description is only an overview of the technical solutions of the present application, so the technical means of the present application can be more clearly understood, and can be implemented in accordance with the contents of the present disclosure. In addition, to make the above and other objects, features and advantages of the present application more clearly understood, some specific embodiments of the present application are described in detail below.
Brief Description of the Drawings
[48] The optional embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Various other advantages and benefits of the present invention will become apparent to a person skilled in the art based on the following description.
The drawings are only for the purpose of illustrating some embodiments and are not to be considered as limiting the present invention. Throughout the drawings, the same reference numerals are used to refer to the same parts. In the drawing:
[49] FIG. 1 is a flow chart showing the steps of an information recommendation method according to an embodiment of the present application.
[50] FIG 2 is a flow chart showing the steps for determining an active time range of a user according to an embodiment of the present application.
[51] FIG. 3 is a flow chart showing the steps for determining an unfamiliar region of a user according to an embodiment of the present application.
[52] FIG. 4 is a flow chart showing the steps of an information recommendation method according to another embodiment of the present application.
[53] FIG. 5 is a flow chart showing the steps of an information recommendation method according to yet another embodiment of the present application.
[54] FIG. 6 is a structural block diagram of an information recommendation device according to an embodiment of the present application.
[55] FIG. 7 is a structural block diagram of another information recommendation device according to another embodiment of the present application.
[56] FIG. 8 is a structural block diagram of an information recommendation device according to yet another embodiment of the present application.
[57] FIG. 9 is a structural block diagram of an information recommendation device according to yet another embodiment of the present application.
[58] FIG. 10 is a block diagram of a computing device 1500 of the present application.
Description of the Embodiments
[59] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. It should be understood that the present disclosure may be implemented in many different ways, and thus not be limited to the embodiments described herein. Rather, the embodiments are provided in order to allow a more complete understanding of the present disclosure, and the scope of the present disclosure can be fully understood by a person skilled in the art.
[60] In the existing solution, when a user accesses an APP in a mobile terminal, the accessed APP can obtain the current location of the user, and recommend POI information near the current location to the user. For example, if the user accesses a restaurant APP, the restaurant APP can send recommendations of the restaurants within 500 meters of the current location. However, the existing solution does not consider whether the user currently needs such POI
information, resulting in waste of network resources caused by transmitting unnecessary POI
information, and disturbing the user.
[61] In order to reduce the waste of the network resources caused by the transmission of the unnecessary POI information, and avoid interrupting the user, this embodiment of the present application first determines the current time and the current geographical region where the user is located, if the current time is within an active time range of the user and current geographical region is an unfamiliar region for the user, the user may be considered to have the need for the POI information. In this case, the POI information of the current geographical region will be recommended to the user. In this way, not only can an accurate delivery of POI
information be realized, but also the waste of network resources and the disturbance to user caused by irrelevant POI information recommendation can be reduced.
[62] Referring to FIG. 1, which is a flow chart showing the steps of an information recommendation method according to an embodiment of the present application, the method may comprise the following steps:
[63] Step 101 includes obtaining a current time and a current geographical region in which a user is located;
[64] Step 102 includes, if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region.
[65] The embodiment of the present application can be applied to a mobile terminal to intelligently recommend POI information to a user through a mobile terminal, thereby saving network resources of the mobile terminal and improving user experience of using the mobile terminal. The mobile terminal may be any mobile terminal such as a smart phone, a tablet computer, or a notebook computer. The embodiment of the present application does not limit the specific mobile terminal. For convenience of description, the embodiment of the present application uses a smart phone as an example to describe the information recommendation method, and the information recommendation methods corresponding to other mobile terminals may refer to each other.
[66] In the embodiment of the present application, the active time range may be used to reflect a high frequency time period of the user's access behavior. For example, if the current time acquired by the dining APP is within the active time range of the user, the user may be considered to have a tendency to find a nearby restaurant in the dining APP, that is, the user has the POI information requirement, and the dining APP may recommend the POI
information to the user. The recommended POI information may include: restaurant information near the current geographic area where the user is located.
[67] In the embodiment of the present application, the unfamiliar area can be used to reflect the low frequency geographical area of the user activity. If the user is in the unfamiliar area, the user is not familiar with the POI information in the area, and the POI information can be recommended to the user.
[68] The embodiment of the present application can determine whether the user has the POI
information in the current time and the current geographic area based on the active time range of the user and the unfamiliar area of the user, and can not only accurately recommend the POI
information, but also reduce the waste of network resources and the interruptions to users.
[69] In an actual application, when a user accesses an APP in a mobile terminal, such as a dining APP, the accessed APP may record the corresponding access information to the access log, where the access information may specifically include: an access time, the location information (such as the latitude and longitude, the street address, and the like), the source APP, or the URL
(Uniform Resource Locator) address of the page, etc., so that the historical access of the user in the preset time period can be collected in advance in the embodiment of the present application logs, and analyzes the collected historical access logs to get the user's active time range and the user's unfamiliar area.
[70] In the embodiment of the present application, the historical access log may be from not only one APP in the mobile terminal (such as a dining APP), but also may be from multiple APPs in the mobile terminal (such as a dining APP, a navigation APP, and a shopping APP etc.).
Alternatively, the historical access log may also come from one or more of the user's multiple mobile terminals. For example, the user logs in to the APP in the plurality of mobile terminals by using the user account, and the embodiment of the present application may collect the historical access log of the APP records in the plurality of mobile terminals of the user by using the user account. It can be understood that the specific collection manner of the user's historical access log in the preset time period is not limited in the embodiment of the present application. The preset time period may be a recent period of time, such as the last month, the last three months, or the last six months, etc.; it can be understood that the embodiment of the present application does not limit the length of the preset time period.
[71] As shown in FIG. 2, in an optional embodiment of the present application, the active time range of the user may be determined by the following steps:
[72] Step Sll includes obtaining a historical access log of the user within a preset time period, and extracting access time points corresponding to the historical access log.
[73] Wherein the historical access log may include an access log generated by the user through any access behavior performed by the mobile terminal, for example, the access log generated by the user accessing the APP, or clicking on the merchant list or the merchant page, or invoking the location service to locate the mobile terminal, or by reservation or transaction or any other access behaviors. It can be understood that the specific content of the historical access log is not limited in the embodiment of the present application.
[74] Specifically, the APP in the mobile terminal can obtain all the historical access logs of the user in the most recent month, and filter out the historical access log with the access time.
[75] Step S12 includes clustering the extracted access time points to obtain a time point set satisfying a first density condition, wherein the first density condition comprises: the time point set comprises access time points in a number exceeding a first threshold, a time interval between any two access time points in the time point set is less than a preset interval.
[76] Optionally, the embodiment of the present application uses DBScan (Density-Based Spatial Clustering of Applications with Noise) to cluster the access time points. The algorithm utilizes the concept of density-based clustering, requiring that the number of objects (points or other spatial objects) contained in a certain region of the cluster space is not less than a given threshold.
It can be understood that the specific clustering algorithm is not limited in the embodiment of the present application. For example, an OPTICS (object sorting) clustering algorithm, a DENCLUE
(density distribution function) clustering algorithm, and the like may also be used.
[77] For example, if the preset interval is 30 seconds and the first threshold is 4, the time point set obtained after the clustering satisfies the first density condition, and the access time point exists within the time interval 30 seconds, and the number of access time points existing in the 30-second time interval is greater than or equal to 4, and the obtained time point set includes a high-frequency time point of the user access behavior, and the high-frequency time point can reflect the active time of the user's access behavior.
[78] Step S13 includes counting the access time points in the time point set to determine the active time range of the user.
[79] Specifically, the embodiment of the present application may perform statistics on the access time points in the time point set, and calculate an average value, for example, calculate an average value according to the access time point in the time point set to be 12:00 on Sunday. In an actual application, the actual access time of the user is not fixed at a specific time point.
Therefore, the embodiment of the present application floats up and down the appropriate time period on the basis of the average value to obtain a more realistic active time range. For example, the access time points in the set of time points are mostly distributed at 11:20 to 13:30 on Sunday, and in combination with the average, it can be determined that the active time range of the user is from 11:00 to 13:00 on Sunday, the active time range can reflect the high frequency time period of the user's access behavior. If the current time is within the active time range of the user, the user may be considered to have the need for POI information at the current time.
[80] It can be understood that the time period of the above-mentioned floating time may be determined according to the distribution of the access time points, or may be determined according to the actual life experience, which is not limited by the embodiment of the present application. For example, for a dining app, the user typically has access requirements during the time range from lunch (11:00 to 13:00) or dinner (17:00 to 19:00), and the like.
[81] In the embodiment of the present application, when calculating the average value of the access time points in the time point set, the calculation may be performed according to all the access time points in the time point set, or remove the maximum and minimum values and then calculate the average value to avoid the influence of individual extreme points on the average value and improve the accuracy of the active time range. It can be understood that the specific manner of calculating the average value of the access time points in the set of time points is not limited in the embodiment of the present application. Of course, the above-mentioned statistics are used to calculate the access time points in the set of time points, and the active time range of the user is determined as an application example of the present application.
The specific manner of performing statistics is not limited. For example, the access time point in the set of time points may be counted by using standard deviations.
[82] In the embodiment of the present application, when the user accesses the APP in the mobile terminal, the APP may collect the historical access log of the user, and analyze the historical access log of the user to obtain an unfamiliar area of the user, for example, the unfamiliar area may be an area other than the familiar area, which may include a work area, a living area, and the like. If the current geographic area in which the user is located is the unfamiliar area of the user, the user is not familiar with the POI in the area, and therefore, the user may be considered to have the POI information requirement at the current time.
[83] As shown in FIG. 3, in an optional embodiment of the present application, the unfamiliar region of the user may be determined by the following steps:
[84] Step S21 includes obtaining the historical access log of the user within a preset time period, and determining a location track corresponding to the historical access log.
[85] The historical access log may include an access log generated by the user through any = access behavior performed by the mobile terminal, for example, an access log generated by the user accessing the APP, or clicking on the merchant list or the merchant page, or invoking the location service to locate the mobile terminal or reservation or transaction on the merchant page or any other access behaviors. It can be understood that the specific content of the historical access log is not limited in the embodiment of the present application.
[86] Specifically, the APP in the mobile terminal can obtain all historical access logs of the user in the most recent month, and filter out historical access logs with latitude and longitude information. For example, the access information recorded in a historical access log includes latitude and longitude information, and the latitude and longitude information is:
(34.2294710000, 108.9538400000). Based on the latitude and longitude information, it can be determined that the corresponding position is "SAGA Shopping Center", that is, the user has appeared in the "SAGA Shopping Center". The location track of the user corresponding to the historical access log may be obtained according to all the historical access logs with the latitude and longitude information of the user in the most recent month.
[87] Step S22 includes clustering track points in the determined location track according to latitude and longitude thereof to obtain a track point set satisfying a second density condition, wherein the second density condition comprises: track points in a number of more than a second threshold existing in a present coverage range with any one of the track points in the track point set as a circular center.
[88] In the same manner as the access time point clustering, the embodiment of the present application clusters the track points by using a DBScan clustering algorithm.
For example, if the preset coverage is centered on any of the track points, the radius is 500 meters, and the second threshold is 50, then the second density is obtained after clustering. In the set of track points of the condition, there is a track point in the circular coverage with a radius of 500 meters as the center of any track point, and the number of track points is greater than or equal to 50, and the obtained track point set included is the high-frequency location point of the user activity in the user location track, reflecting the geographical location of the user's frequent activities. It can be understood that the shape of the preset coverage is not limited in the present application, and may be, for example, a rectangular area or the like.
[89] Step S23 includes determining the unfamiliar region of the user according to the latitude and longitude of the track points in the track point set.
[90] Specifically, the embodiment of the present application may perform statistics on the latitude and longitude of the track points in the track point set, calculate an average value, and according to the distribution of the track points in the track point set and combined with common sense to obtain the familiar area of the user, and the unfamiliar area of the user can be an area other than the familiar area of the user. The specific statistical process and mode are similar to the statistical process of the access time point, and are not described here.
[91] Optionally, in order to make the determined unfamiliar area more in line with the actual living habits of the user, the embodiment of the present application acquires a historical access log of the user within a preset time period, in addition to the location track corresponding to the historical access log, the access time corresponding to the historical access log may also be acquired. If the track points in the track point set obtained through clustering are mostly distributed between 9 o'clock and 19 o'clock. According to common sense, this time is usually the working time of the user, the track point set may be determined as the working area of the user; if the track points in the track point set are mostly distributed between 19:00 and 8:00, the track point set may be determined as the user's living region.
[92] In summary, based on the existing POI information recommendation based on the user's geographical location, the embodiment of the present application further determines whether the user has the POI information requirement according to the current time and the current geographical area where the user is located. Specifically, if the current time is within the active time range of the user, and the current geographical area is an unfamiliar area to the user, the user may be considered to have a POI information requirement, in which case the user recommends the POI information of the current geographical area, which not only can accurately deliver the POI information, but also can reduce the waste of the network resources and the user's interruption to the irrelevant POI information recommendation.
[93] In this embodiment of the present application, the historical access log of the user may be collected by the mobile terminal, and the historical access log is then analyzed, and the active time range of the user and the unfamiliar region of the user can thus be obtained. Optionally, in order to save the storage space of the mobile terminal and reduce the computing burden of the mobile terminal, in the embodiment of the present application, the historical access log of the user collected by the mobile terminal may be uploaded to a server, and the server analyzes and processes the historical access log of the user. Referring to FIG. 4, a flow chart of steps of an information recommendation method according to another embodiment of the present application is shown, which may specifically include the following steps:
[94] Step 201 includes collecting the historical access log of the user, wherein the historical access log comprises at least a user identifier, an access time, and a location track corresponding to the user access behavior.
[95] In a specific application, when the user accesses the APP in the mobile terminal, the APP in the mobile terminal can record the access log of the user, and save the recorded access log locally in the mobile terminal. The user identifier may be a device identifier corresponding to the mobile terminal of the user, or an identifier of the user account of the user, and the specific content of the user identifier is not limited in the embodiment of the present application.
[96] Step 202 includes uploading, to the server, the historical access log of the user, so that the server determines the active time range and the unfamiliar region of the user according to the historical access log.
[97] Specifically, the mobile terminal may periodically upload the historical access log of the locally stored user to the server in batches, and the historical access log may at least include: a user identifier corresponding to the user access behavior, an access time, and a location track.
[98] The server sorts the historical access logs of the users uploaded by the mobile terminal, filters the error data, and stores them in the server to continuously accumulate the historical access logs of the users. The server analyzes and processes the historical access log of the user in the preset time range, calculates the active time range of the user and the unfamiliar area of the user through the clustering algorithm, and establishes the mapping between the user identifier of the user, the active time range of the user and the user's unfamiliar areas in the server.
[99] Step 203 includes obtaining the active time range and the unfamiliar region of the user from the server.
[100] Specifically, the APP in the mobile terminal may acquire the current time and the current geographical area where the user is located, and acquire an active time range of the user of the user and the user's unfamiliar area from the server corresponding to the user identifier.
[101] Step 204 includes determining if the current time is within an active range of the user, and if yes, go to step 205, if not, go to step 207.
[102] Step 205 includes determining if the current geographical region is unfamiliar for the user, and if yes, go to step 206, if not, go to step 207.
[103] Step 206 includes recommending the point of interest information of the current geographical region to the user.
[104] Step 207 includes not recommending the point of interest information of the current geographical region to the user.
[105] It should be noted that the order of execution of step 204 and step 205 is not limited in the embodiment of the present application, and the two may be executed sequentially, in reverse order, or in parallel.
[106] In an application example of the present application, when a user accesses a dining APP in a smartphone, the dining APP can acquire the current time and the current geographical area where the user is located. In addition, the dining APP may also send the device identifier of the user's smart phone to the dining review server to request the dining review server for the active time range and the familiar area of the user. After receiving the request of the dining APP, the dining review server returns the active time range and the familiar area corresponding to the device identifier of the user's smart phone. If the dining APP determines that the current time is within the active time range of the user, and the current geographical area is an unfamiliar area of the user, recommend the restaurant information of the current geographical area to the user.
[107] In summary, the embodiment of the present application uploads a historical access log of a user collected by a mobile terminal to a server, so that the server analyzes and processes the historical access log of the user, obtains the active time range of the user and the unfamiliar area of the user, and implements the accurate delivery of the POI information.
Moreover, the storage space of the mobile terminal can be saved and the computing burden of the mobile terminal can be reduced on the basis of reducing the waste of the network resources and the interruption of the user by the irrelevant POI information recommendation. In addition, the embodiment of the present application uses a clustering analysis algorithm based on big data to cluster historical access logs of users to ensure the accuracy of clustering results.
[108] Referring to FIG. 5, a flow chart of steps of an information recommendation method according to an embodiment of the present application is shown. Specifically, the method may include the following steps:
[109] Step 301 includes obtaining a dwell time of the user in the current geographical region.
[110] Step 302 includes, if the current time is within an active time range of the user and the current geographical region is an unfamiliar region to the user, and if the dwell time exceeds a preset time threshold, recommending, to the user, information of the point of interest (POI) in the current geographical region.
[111] In addition to determining whether to recommend POI information to the user according to the active time range of the user and the familiar area of the user, the embodiment of the present application may also determine according to the user's dwell time in the current geographical area. The dwell time can be used to reflect the user's access tendency. For example, if the user stays in a mall for more than 30 minutes, the user may be considered to have a tendency to consume at the mall, and the merchant information in the mall may be recommended to the user.
If the user's dwell time in the mall is only 5 minutes, the user may be considered not to have a tendency to consume the mall, and the merchant information in the mall may not be recommended to the user.
[112] It should be noted that, for the method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the embodiments of the present application are not subject to the limitations of the described action sequence, because certain steps may be performed in other sequences or concurrently in accordance with embodiments of the present application. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required in the embodiments of the present application.
[113] FIG. 6 is a structural block diagram of an information recommendation apparatus according to an embodiment of the present application, which may specifically include the following modules:
[114] a first obtaining module 401, which is used for obtaining a current time and a current geographical region in which a user is located;
[115] a first recommending module 402, which is used for, if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region.
[116] Optionally, as shown in FIG. 7, the device may further include:
[117] an active time range determining module 501, which is used for determining the active time range of the user;
[118] the active time range determining module 501 comprises:
[119] a first obtaining submodule 5011, which is used for obtaining a historical access log of the user within a preset time period, and extracting access time points corresponding to the historical access log;
[120] a first clustering submodule 5012, which is used for clustering the extracted access time points to obtain a time point set satisfying a first density condition, wherein the first density condition comprises: the time point set comprises access time points in a number exceeding a first threshold, and a time interval between any two access time points in the time point set is less than a preset interval;
[121] a first counting submodule 5013, which is used for counting the access time points in the time point set to determine the active time range of the user.
[122] Optionally, the device may further include:
[123] an unfamiliar region determining module 502, which is used for determining an unfamiliar region of the user;
[124] the unfamiliar region determining module 502 comprises:
[125] a second obtaining submodule 5021, which is used for obtaining the historical access log of the user within a preset time period, and determining a location track corresponding to the historical access log;
[126] a second clustering submodule 5022, which is used for clustering track points in the determined location track according to latitude and longitude thereof to obtain a track point set satisfying a second density condition, wherein the second density condition comprises: track points in a number of more than a second threshold existing in a present coverage range with any one of the track points in the track point set as a circular center;
[127] a second counting submodule 5023, which is used for determining the unfamiliar region of the user according to the latitude and longitude of the track points in the track point set.
[128] Optionally, as shown in FIG. 8, the device may further include:
[129] a collecting module 601, which is used for collecting the historical access log of the user, wherein the historical access log comprises at least a user identifier, an access time, and a location track corresponding to the user access behavior;
[130] an uploading module 602, which is used for uploading, to the server, the historical access log of the user, so that the server determines the active time range and the unfamiliar region of the user according to the historical access log;
[131] a second obtaining module 603, which is used for obtaining the active time range and the unfamiliar region of the user from the server.
[132] Referring to FIG. 9, a structural block diagram of an information recommendation device according to an embodiment of the present application is shown, which may specifically include the following modules:
[133] a first obtaining module 401, which is used for obtaining a current time and a current geographical region in which a user is located;
[134] a second recommending module 403, which is used for obtaining a dwell time of the user in the current geographical region if the current time is within an active time range of the user and the current geographical region is an unfamiliar region of the user; and if the dwell time exceeds a preset time threshold, recommending, to the user, information of the point of interest (POI) in the current geographical region.
[135] For the device embodiments shown in FIG. 6 to FIG. 9, since they are basically similar to the method embodiments shown in FIG. 1 to FIG. 5, the description is relatively simple, and the related part may be refer to the description of the methods as is shown in FIG. 1 to FIG. 5.
[136] An embodiment of the present application provides a computing device, including: a memory, a processor, and a program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the information recommendation method as shown in FIG. 1 to FIG. 5.
[137] Referring to FIG. 10, a schematic structural diagram of a computing device 1500 of the present application is shown. Specifically, it may include: at least one processor 1501, a memory 1502, at least one network interface 1504, and a user interface 1503. The various components in computing device 1500 are connected together by a bus system 1505. It will be appreciated that the bus system 1505 is used to implement connection and communication between these components. The bus system 1505 may include a power bus, a control bus, and a status signal bus in addition to a data bus. However, for clarity of the description, various buses are labeled as bus system 1505 in FIG. 10.
[138] The user interface 1503 may include a display, a keyboard, or a pointing device (such as a mouse, a trackball, a touchpad, or a touch screen).
[139] It is to be understood that the memory 1502 in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be a read-only memory (ROM), a programmable read only memory (PROM), an erasable programmable read only memory (Erasable PROM, EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM) that acts as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (Synchronous DRAM, or SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink connection dynamic random access memory (SLDRAM), and direct memory bus random access memory (DRRAM).
Memory 1502 of the systems and methods described in the embodiments of the application is intended to comprise, without being limited to, these and any other suitable types of memory.
[140] In some implementations, the memory 1502 stores elements, executable modules or data structures, a subset thereof, or an extended set thereof: an operating system 15021 and an application 15022.
[141] The operating system 15021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application 15022 includes various applications, such as a media player, a browser, and the like for implementing various application services. A program implementing the method of the embodiments of the present application may be included in the application 15022.
[142] In the embodiments of the present application, by calling the program or instruction stored in the memory 1502, specifically, the program or instruction stored in the application 15022, the processor 1501 is configured to acquire the current time and the current geographical region where the user is located; and if the current time is within the active time range of the user, and the current geographical region is an unfamiliar region to the user, the point of interest information of the current geographical region would be recommended to the user.
[143] A computer readable storage medium having stored thereon a program is provided, wherein the program is executed by a processor to implement the steps of the information recommendation method shown in FIG. 1 to FIG. 5.
[144] The method disclosed in the foregoing embodiments of the present application may be applied to the processor 1501 or implemented by the processor 1501. The processor 1501 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the foregoing method may be completed by an integrated logic circuit of hardware in the processor 1501 or an instruction in a form of software. The processor 1501 may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or another programmable logic device, a discrete gate or transistor logic device, a discrete hardware component to implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or may be any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by the hardware decoding processor, or may be performed by a combination of hardware and software modules in the decoding processor. The software module can be located in a conventional storage medium such as random access memory, flash memory, read only memory, programmable read only memory or electrically erasable programmable memory, registers, and the like. The storage medium is located in the memory 1502, and the processor 1501 reads the information in the memory 1502 and performs the steps of the above method in combination with its hardware.
[145] It can be understood that the embodiments described in the embodiments of the present application can be implemented by hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSP devices, DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein or a combination thereof
[146] For the software implementation, the technology described in the embodiments of the present application can be implemented by a module (for example, a procedure, a function, and the like) that performs the functions described in the embodiments of the present application.
The software code can be stored in memory and executed by the processor. The memory can be implemented in the processor or external to the processor.
[147] Optionally, the processor 1501 may be further configured to determine an active time range of a user through the following steps:
[148] obtaining a historical access log of the user within a preset time period; and extracting access time points corresponding to the historical access log;
[149] clustering the extracted access time points to obtain a time point set satisfying a first density condition, wherein the first density condition comprises: the time point set comprises access time points in a number exceeding a first threshold, a time interval between any two access time points in the time point set is less than a preset interval;
[150] counting the access time points in the time point set to determine the active time range of the user.
[151] Optionally, the processor 1501 may be further configured to determine the unfamiliar region of the user through the following steps:
[152] obtaining the historical access log of the user within a preset time period; and determining a location track corresponding to the historical access log;
[153] clustering track points in the determined location track according to latitude and longitude thereof to obtain a track point set satisfying a second density condition, wherein the second density condition comprises: track points in a number of more than a second threshold existing in a present coverage range with any one of the track points in the track point set as a circular center;
[154] determining the unfamiliar region of the user according to the latitude and longitude of the track points in the track point set.
[155] Optionally, the processor 1501 is further configured to perform collecting the historical access log of the user, wherein the historical access log comprises at least a user identifier, an access time, and a location track corresponding to the user access behavior;
uploading, to the server, the historical access log of the user, so that the server determines the active time range and the unfamiliar region of the user according to the historical access log;
and obtaining the active time range and the unfamiliar region of the user from the server.
[156] Optionally, the processor 1501 is further configured to perform if the current time is within an active time range of the user and the current geographical region is an unfamiliar region of the user, and if the dwell time exceeds a preset time threshold, recommending, to the user, information of the point of interest (POI) in the current geographical region.
[157] The embodiment of the present application further provides a computer readable storage medium, where a program is stored, and when the program is executed by the processor, the following steps are performed: obtaining a current time and a current geographical region in which a user is located; if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region.
[158] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems may also be used along with the teaching provided herein. The structure required to construct such a system is apparent from the above description. Moreover, this application is not directed to any particular programming language. It should be understood that the content of the present application described herein may be implemented in a variety of programming languages, and the description of the specific language above is for the purpose of illustrating the preferred embodiments.
[159] In the description provided herein, numerous specific details are set forth. However, it is understood that the embodiments of the present application may be implemented without these specific details. In some examples, some well-known methods, structures, and techniques are not shown in detail so as not to distract from the main contents of the present description.
[160] Similarly, it should be understood that in order to simplify the present disclosure and help understand one or more of the various inventive aspects thereof, in the above description for the exemplary embodiments of the present application, various features of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, the method disclosed is not to be interpreted as reflecting the intention that the claimed invention requires more features than those specifically recited in the claims. Rather, as the following claims reflect, inventive aspects reside in less than all features of the embodiments disclosed herein. Therefore, the claims following the specific embodiments are hereby explicitly incorporated into the specific embodiments, and each claim would be a separate embodiment of the present application.
[161] A person skilled in the art will appreciate that the modules in the devices of the embodiments can be adaptively changed and placed in one or more devices different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component, or they may be divided into a plurality of sub-modules or sub-units or sub-components. In addition to such features and/or at least some of the processes or units being mutually exclusive, any combination of the features disclosed in the specification, including the accompanying claims, the abstract and the drawings, and any methods disclosed, or processes or units of the device may be combined. Each feature disclosed in this description (including the accompanying claims, the abstract and the drawings) may be replaced by alternative features that can provide the same, equivalent or similar purpose.
[162] In addition, a person skilled in the art will appreciate that, although some embodiments described herein include certain features that are included in other embodiments, combinations of features of different embodiments are intended to be within the scope of the present application, and different embodiments may be formed. For example, in the following claims, any one of the claimed embodiments can be used in any combination.
[163] The various component embodiments of the present application can be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof. A person skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components of the information recommendation method and device in accordance with the embodiments of the present application. The application can also be implemented as a device or device program (e.g., a program and a program product) for performing some or all of the methods described herein. Such a program implementing the present application may be stored on a computer readable storage medium or may be in the form of one or more signals. Such signals may be downloaded from an internet platform, provided on a carrier signal, or provided in any other form.
[164] It should be noted that the above-described embodiments are illustrative of the present application and are not intended to limit the scope of the present application. A person skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as a limitation. The word "comprising" does not exclude the presence of the elements or steps that are not recited in the claims. The word "a" or "an" before an element does not exclude that there are a plurality of such elements. The present application can be implemented by means of hardware comprising several distinct elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same hardware item. The use of the words first, second, and third does not indicate any order. These words can be interpreted as names.

Claims (12)

Claims
1. A method for recommending information, characterized in that the method comprises:
obtaining a current time and a current geographical region in which a user is located;
if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region.
2. The method for recommending information according to claim 1, characterized in that the method further comprises:
obtaining a historical access log of the user within a preset time period;
extracting access time points corresponding to the historical access log;
clustering the extracted access time points to obtain a time point set satisfying a first density condition, wherein the first density condition comprises:
the time point set comprises access time points in a number exceeding a first threshold, a time interval between any two access time points in the time point set is less than a preset interval; and counting the access time points in the time point set to determine the active time range of the user.
3. The method for recommending information according to claim 1, characterized in that the method further comprises:
obtaining the historical access log of the user within a preset time period;
determining a location track corresponding to the historical access log;
clustering track points in the determined location track according to latitude and longitude thereof to obtain a track point set satisfying a second density condition, wherein the second density condition comprises: track points in a number of more than a second threshold existing in a present coverage range with any one of the track points in the track point set as a circular center;

determining the unfamiliar region of the user according to the latitude and longitude of the track points in the track point set.
4. The method for recommending information according to claim 1, characterized in that the method further comprises:
collecting the historical access log of the user, wherein the historical access log comprises at least a user identifier, an access time, and a location track corresponding to the user access behavior;
uploading, to the server, the historical access log of the user, so that the server determines the active time range and the unfamiliar region of the user according to the historical access log;
obtaining the active time range and the unfamiliar region of the user from the server.
5. The method for recommending information according to any one of claims 1 to 4, characterized in that the if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region, comprising:
obtaining a dwell time of the user in the current geographical region, if the current time is within an active time range of the user and the current geographical region is an unfamiliar region of the user;
if the dwell time exceeds a preset time threshold, recommending, to the user, information of the point of interest (POI) in the current geographical region.
6. A device for recommending information, characterized in that the device comprises:
a first obtaining module, which is used for obtaining a current time and a current geographical region in which a user is located;
a first recommending module, which is used for, if the current time falls within an active time range of the user, and the current geographical region is a region with which the user is unfamiliar, recommending, to the user, information of a point of interest (POI) in the current geographical region.
7. The device according to claim 6, characterized in that the device further comprises:

an active time range determining module, which is used for determining the active time range of the user;
the active time range determining module comprises:
a first obtaining submodule, which is used for obtaining a historical access log of the user within a preset time period, and extracting access time points corresponding to the historical access log;
a first clustering submodule, which is used for clustering the extracted access time points to obtain a time point set satisfying a first density condition, wherein the first density condition comprises:
the time point set comprises access time points in a number exceeding a first threshold, and a time interval between any two access time points in the time point set is less than a preset interval; and a first counting submodule, which is used for counting the access time points in the time point set to determine the active time range of the user.
8. The device according to claim 6, characterized in that the device further comprises:
an unfamiliar region determining module, which is used for the unfamiliar region of the user;
the unfamiliar region determining module comprises:
a second obtaining submodule, which is used for obtaining the historical access log of the user within a preset time period, and determining a location track corresponding to the historical access log;
a second clustering submodule, which is used for clustering track points in the determined location track according to latitude and longitude thereof to obtain a track point set satisfying a second density condition, wherein the second density condition comprises: track points in a number of more than a second threshold existing in a present coverage range with any one of the track points in the track point set as a circular center;
a second counting submodule, which is used for determining the unfamiliar region of the user according to the latitude and longitude of the track points in the track point set.
9. The device according to claim 6, characterized in that the device further comprises:
a collecting module, which is used for collecting the historical access log of the user, wherein the historical access log comprises at least a user identifier, an access time, and a location track corresponding to the user access behavior;
an uploading module, which is used for uploading, to the server, the historical access log of the user, so that the server determines the active time range and the unfamiliar region of the user according to the historical access log;
a second obtaining module, which is used for obtaining the active time range and the unfamiliar region of the user from the server.
10. The device according to any one of claims 6 to 9, characterized in that the device further comprises:
a second recommending module, which is used for obtaining a dwell time of the user in the current geographical region if the current time is within an active time range of the user and the current geographical region is an unfamiliar region to the user; and if the dwell time exceeds a preset time threshold, recommending, to the user, information of the point of interest (POI) in the current geographical region.
11. A computing device, comprising: a memory, a processor, and a program stored on the memory and executable on the processor, characterized in that the processor executes the program to implement the steps in the method for recommending information according to any one of claims 1 to 5.
12. A computer readable storage medium, having stored thereon a program, characterized in that the program is executed by a processor to implement the steps in the method for recommending information according to any one of claims 1 to 5.
CA3064137A 2017-06-26 2017-12-29 Method and device for recommending information Pending CA3064137A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
CN201710496441.9 2017-06-26
CN201710496441.9A CN107491474A (en) 2017-06-26 2017-06-26 Information recommendation method and device
PCT/CN2017/119939 WO2019000887A1 (en) 2017-06-26 2017-12-29 Method and device for recommending information

Publications (1)

Publication Number Publication Date
CA3064137A1 true CA3064137A1 (en) 2019-01-03

Family

ID=60643675

Family Applications (1)

Application Number Title Priority Date Filing Date
CA3064137A Pending CA3064137A1 (en) 2017-06-26 2017-12-29 Method and device for recommending information

Country Status (7)

Country Link
US (1) US10795957B2 (en)
EP (1) EP3623985A4 (en)
JP (1) JP6987891B2 (en)
KR (1) KR20200006584A (en)
CN (1) CN107491474A (en)
CA (1) CA3064137A1 (en)
WO (1) WO2019000887A1 (en)

Families Citing this family (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110392335B (en) * 2018-04-12 2022-02-11 阿里巴巴集团控股有限公司 Step-counting data processing method and device
CN108960785B (en) * 2018-07-13 2020-10-27 维沃移动通信有限公司 Information prompting method and device
CN109344339B (en) * 2018-09-28 2022-03-18 中山乐心电子有限公司 Method and system for publishing dynamic activity information and recommending method
CN109614556B (en) * 2018-10-31 2020-03-13 拉卡拉支付股份有限公司 Access path prediction and information push method and device
KR102052452B1 (en) * 2019-03-26 2019-12-05 민지연 Performance information providing system
CN110334167B (en) * 2019-06-26 2023-06-09 浪潮软件集团有限公司 Position deviation early warning method and device based on neural network track
CN111190940B (en) * 2019-12-27 2024-04-02 中国平安人寿保险股份有限公司 Discrete data processing method, device, equipment and medium for user access
CN111737602A (en) * 2020-06-19 2020-10-02 中国银行股份有限公司 Bank branch information pushing method and device
US11429798B2 (en) * 2020-08-10 2022-08-30 Innolux Corporation Wireless tag location system and method thereof
CN112148808B (en) * 2020-09-28 2024-02-27 杭州海康威视系统技术有限公司 Relationship construction method and device and electronic equipment
CN113052660A (en) * 2020-09-29 2021-06-29 浙江口碑网络技术有限公司 Method and device for generating shared data circle
CN112560910B (en) * 2020-12-02 2024-03-01 中国联合网络通信集团有限公司 User classification method and device
CN112464096A (en) * 2020-12-03 2021-03-09 北京五八信息技术有限公司 Information processing method and device
CN112559859B (en) * 2020-12-08 2023-06-30 杭州海康威视系统技术有限公司 Resource recommendation method, device, electronic equipment and machine-readable storage medium
CN112581060A (en) * 2020-12-22 2021-03-30 北京优挂信息科技有限公司 Cargo allocation demand degree detection method, device and equipment based on vehicle loading and unloading points
CN112712392A (en) * 2020-12-31 2021-04-27 京东数字科技控股股份有限公司 Message pushing method and device, electronic equipment and storage medium
CN112991008A (en) * 2021-03-04 2021-06-18 北京嘀嘀无限科技发展有限公司 Position recommendation method and device and electronic equipment
CN113312563B (en) * 2021-06-24 2022-09-16 北京三快在线科技有限公司 Information recommendation method, device, equipment and storage medium
CN113742557A (en) * 2021-08-10 2021-12-03 北京深演智能科技股份有限公司 Method and device for recommending application program identification rules
CN113407858B (en) * 2021-08-20 2021-12-21 明品云(北京)数据科技有限公司 Information push method, system, medium and electronic device
CN113900906A (en) * 2021-10-28 2022-01-07 北京达佳互联信息技术有限公司 Log capacity determination method and device, electronic equipment and storage medium
CN114359876B (en) * 2022-03-21 2022-05-31 成都奥伦达科技有限公司 Vehicle target identification method and storage medium
CN115134407A (en) * 2022-06-27 2022-09-30 平安银行股份有限公司 Active region determination method and device, computer equipment and storage medium

Family Cites Families (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004199667A (en) * 2002-12-04 2004-07-15 Matsushita Electric Ind Co Ltd Information providing device and its method
CN103279470B (en) * 2003-02-19 2016-08-10 松下电器(美国)知识产权公司 Mobile terminal apparatus, server unit, information providing system and method
US7962280B2 (en) * 2005-09-12 2011-06-14 Panasonic Corporation Map displaying device
EP2513603A1 (en) 2009-12-15 2012-10-24 Mapquest, Inc. Computer-implemented methods and systems for mult-level geographic query
CN102685662A (en) 2011-03-17 2012-09-19 高德软件有限公司 Position-based discount coupon management platform, releasing method and releasing system and intelligent terminal
US8335524B2 (en) * 2011-04-29 2012-12-18 Navteq B.V. Method and system for providing location targeted advertisements
EP2541484B1 (en) * 2011-06-30 2023-02-15 Orange Geo-spatial recommendation and discovery system
US9317834B2 (en) 2011-06-30 2016-04-19 Microsoft Technology Licensing, Llc User computing device with personal agent program for recommending meeting a friend at a service location based on current location, travel direction, and calendar activity
CN103905978B (en) 2012-12-27 2018-03-23 中国电信股份有限公司 Location-based information-pushing method, pusher and network
JP2014192587A (en) * 2013-03-26 2014-10-06 Zenrin Datacom Co Ltd Information distribution device, information distribution method and program
CN104102638B (en) * 2013-04-02 2017-06-20 北京百度网讯科技有限公司 Method for pushing, system and device based on positional information
US20150332325A1 (en) * 2013-04-19 2015-11-19 xAd, Inc. System and Method for Visualizing Real-Time Location-Based Events
CN104636354B (en) * 2013-11-07 2018-02-06 华为技术有限公司 A kind of position interest points clustering method and relevant apparatus
CN104008184A (en) * 2014-06-10 2014-08-27 百度在线网络技术(北京)有限公司 Method and device for pushing information
CN105450594A (en) 2014-08-12 2016-03-30 北京拉手网络技术有限公司 Group buying voucher information push method and user equipment
CN104484817B (en) 2014-12-22 2019-06-21 北京大唐智能卡技术有限公司 A kind of advertisement information processing method, advertisement services server and system
US20160379293A1 (en) 2015-06-29 2016-12-29 International Business Machines Corporation Application for automatic ordering of food items
CN106528559B (en) * 2015-09-10 2020-04-24 阿里巴巴集团控股有限公司 Method and device for providing position information
CN105490926A (en) 2015-12-30 2016-04-13 哈尔滨工业大学 User behavior analysis and information push system based on position service
CN105488233A (en) * 2016-01-25 2016-04-13 广东顺德中山大学卡内基梅隆大学国际联合研究院 Reading information recommendation method and system
CN106484848B (en) 2016-09-30 2020-07-10 网易传媒科技(北京)有限公司 Application recommendation method and device
US10417691B2 (en) * 2016-10-31 2019-09-17 Walmart Apollo, Llc System, method, and non-transitory computer-readable storage media for automatically checking in a customer

Also Published As

Publication number Publication date
JP6987891B2 (en) 2022-01-05
JP2020523696A (en) 2020-08-06
US20200104333A1 (en) 2020-04-02
EP3623985A1 (en) 2020-03-18
WO2019000887A1 (en) 2019-01-03
US10795957B2 (en) 2020-10-06
KR20200006584A (en) 2020-01-20
EP3623985A4 (en) 2020-07-22
CN107491474A (en) 2017-12-19

Similar Documents

Publication Publication Date Title
CA3064137A1 (en) Method and device for recommending information
US11468019B2 (en) Apparatus, systems, and methods for analyzing characteristics of entities of interest
US9275114B2 (en) Apparatus and method for profiling users
Jiang et al. Zipf's law for all the natural cities in the United States: a geospatial perspective
US20170206204A1 (en) System, method, and device for generating a geographic area heat map
US20170010123A1 (en) Hybrid road network and grid based spatial-temporal indexing under missing road links
CN107885873B (en) Method and apparatus for outputting information
WO2015126896A1 (en) Creating a geographic heatmap
CN107430631B (en) Determining semantic place names from location reports
CN107220308B (en) Method, device and equipment for detecting rationality of POI (Point of interest) and readable medium
US20190147468A1 (en) Location evaluation
JP2010009315A (en) Recommended store presentation system
CN112069281A (en) Method and device for determining position of interest point, computer equipment and storage medium
CN108174350B (en) Positioning method and device
Uphaus et al. Location-based services–the market: success factors and emerging trends from an exploratory approach
Wang et al. A GIS-based analytical framework for evaluating the effect of COVID-19 on the restaurant industry with big data
CN114547097A (en) Data processing method, device, equipment and storage medium
US20200300654A1 (en) Objective generation of a point of interest score based on quantities of user stops
CN106937308B (en) Method and equipment for determining user access service area and activity information
US11856473B2 (en) Intelligent geofence provisioning
US9588988B2 (en) Visual indicators for temporal context on maps
Lafazani et al. Applying multiple and logistic regression models to investigate periurban processes in Thessaloniki, Greece
CN110784392B (en) Method and equipment for acquiring reading reminding information
CN110619086B (en) Method and apparatus for processing information
Chen et al. A case study for Beijing point of interest data using group linked Cox process

Legal Events

Date Code Title Description
EEER Examination request

Effective date: 20220505

EEER Examination request

Effective date: 20220505

EEER Examination request

Effective date: 20220505

EEER Examination request

Effective date: 20220505

EEER Examination request

Effective date: 20220505

EEER Examination request

Effective date: 20220505